This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Funded through a subcontract the BTP, the collaboration with Professor J. Rehr focuses on improvements in theory of EXAFS and edge studies of biological systems. Specifically it is aimed at the development of more quantitative XANES analysis tools to complement the present tools for EXAFS, e.g., the SSRL EXAFSPAK software combined with the ab initio x-ray spectroscopy codes FEFF. Current analyses of XAS are typically based on traditional least-squares fitting procedures. However, these methods can be problematic for biological structures since they involve large numbers of correlated variables. This limits their effectiveness and can lead to an ill-conditioned fitting problem. As an alternative, development of a Bayesian method-based approach was begun, which has several advantages. In particular, the method takes advantage of a priori estimates of the model parameters and their uncertainties, avoids the restriction on the size of the model parameter space, and can be automated. The goal is to develop such automated analyses of both the x-ray absorption fine structure (EXAFS) and near edge structure (XANES) of biological structures.